Introduction to swirl

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

EJ

Excellent course! I already knew a lot about R - but this class helped me solidify what I already knew, taught me lots of new tricks, and now I have a certificate that says I know `something' about R!

GB

Feb 03, 2016

Filled StarFilled StarFilled StarFilled StarFilled Star

Excelente opportunity to learn a lot. The course is very well prepared introduce you to R programing. Dont feel bad if you dont get it at te first moment. It will be a process of leaning worth trying

수업에서

Week 1: Background, Getting Started, and Nuts & Bolts

This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story.

강사:

Roger D. Peng, PhD

Associate Professor, Biostatistics

Jeff Leek, PhD

Associate Professor, Biostatistics

Brian Caffo, PhD

Professor, Biostatistics

스크립트

Hi, everyone. I just want to introduce a experimental feature that we've, that we've developed for the R programming class. It's called Statistics with Interactive R Learning or SWIRL for short. And it's, and it was developed by Nick Carchedi, who's a student here at the Johns Hopkins department of bio-statistics. This is a system that allows you to kind of interactively learn R at your own pace. And it will walk you through a, a bunch of lessons about different aspects of the R language and you can kind of practice as you go. So, rather than kind of watching a lecture and then, you know, doing an assignment and kind of doing things piece by piece, you can actually work on R right in the R console in, in a kind of guided way. Rather than kind of just figuring things out on your own. So, I think this, the SWIRL modules are really helpful and I encourage you to try to walk through them. If you decide to complete them you'll get you'll get a little extra credit through the programming assignment. But the, the modules are absolutely not required. They are totally optional. And so, you don't have to worry about doing them. You can still do perfectly well in the class without doing the SWIRL modules. Nevertheless, I encourage you to try it out. I think it'll be a lot of fun.